Deep Learning with Keras – Part 4: Classification
Classification
Introduction
Welcome to Part 3 of Deep Learning with Keras. The goal of this...
Data Pre-processing for Deep Learning models (Deep Learning with Keras – Part 2)
Link to Part 1.
Dealing with Data
Motivation
Training deep...
Deep Learning with Keras Tutorial – Part 1
About this series
This post is the first part of Deep Learning with Keras series.
This series aims to introduce...
How to Connect Google Colab with Google Drive
In this tutorial, you’ll learn how to connect your Google Colab with Google Drive to build some Deep Learning model on Google...
List of Data Science and Machine Learning GitHub Repositories to Try in 2019
Here is the list of selected Data Science and Machine Learning GitHub Repositories to Try in 2019
Paper with...
Top Artificial Intelligence Books to Read in 2019
1. Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig:
A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory...
21 Free Data Sets/ Projects for Data Science Beginners
We have listed below some of the best datasets/ projects for data science beginners.
1. Enron Emails:
A Few Things To Remember Before Going To Start a Data Science Course
Over the last few years, the data science domain has evolved exponentially. In present times, it has become the backbone of many...
How Generative Adversarial Networks (GANs) work?
Generative Adversarial Networks were first introduced in 2014 in a research paper. They have also been called “the most interesting idea in...
Principal component analysis (PCA) using R
Principal component analysis (PCA) is a statistical analysis technique that uses an orthogonal transformation to convert a set of observations of possibly correlated variables...